Academic Journal

ABSTRACT Combining Link and Content Analysis to Estimate Semantic Similarity

التفاصيل البيبلوغرافية
العنوان: ABSTRACT Combining Link and Content Analysis to Estimate Semantic Similarity
المساهمون: The Pennsylvania State University CiteSeerX Archives
المصدر: http://informatics.indiana.edu/fil/Papers/maps-poster.pdf.
المجموعة: CiteSeerX
مصطلحات موضوعية: Categories and Subject Descriptors, H.3.1 [Information Storage and Retrieval, Content Analysis and Indexing, H.3.3 [Information Storage and Retrieval, Information Search and Retrieval General Terms, Measurement Keywords, Web search, semantic maps, content and link similarity, precision
الوصف: Search engines use content and link information to crawl, index, retrieve, and rank Web pages. The correlations between similarity measures based on these cues and on semantic associations between pages therefore crucially affects the performance of any search tool. Here I begin to quantitatively analyze the relationship between content, link, and semantic similarity measures across a massive number of Web page pairs. Maps of semantic similarity across textual and link similarity highlight the potential and limitations of lexical and link analysis for relevance approximation, and provide us with a way to study whether and how text and link based measures should be combined.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.6876; http://informatics.indiana.edu/fil/Papers/maps-poster.pdf
الاتاحة: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.6876
http://informatics.indiana.edu/fil/Papers/maps-poster.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
رقم الانضمام: edsbas.2C565931
قاعدة البيانات: BASE